Learn about the first performance evaluation of the Intel® Stratix® 10 NX FPGA, optimized for AI. This research compares the Intel Stratix FPGA to current AI-optimized GPUs, NVIDIA* T4 and V100, on a large suite of real-time, deep learning inference workloads.
Read about a proof-of-concept Python*-to-FPGA compiler that is based on the Numba* Just-In-Time (JIT) compiler for Python and the Intel® FPGA SDK for OpenCL™ software technology. It allows for a seamless use of an FPGA card as an accelerator for Python.
This technique uses the Horner scheme to evaluate polynomials and removes the majority of alignment shifters present in FP adders by building a fused evaluation operator. The result is a reduction in circuit latency and logic consumption.